Chemical imaging is a new scientific discipline, which combines the chemical analysis power of optical spectroscopy, including Raman, infrared and fluorescence techniques, with high-resolution optical imaging. It has powerful capability for materials characterization, process monitoring, quality control and disease-state determination. This invention relates to a system for obtaining spectroscopically resolved images of materials, including biological samples, using electronically tunable imaging spectrometers employing liquid crystal elements.
Raman and infrared chemical imaging provide molecular-specific image contrast without the use of stains or dyes. Raman and infrared image contrast is derived from a material's intrinsic vibrational spectroscopic signature, which is highly sensitive to the composition and structure of the material and its local chemical environment. As a result, Raman and infrared imaging can be performed with little or no sample preparation and are widely applicable for materials research, failure analysis, process monitoring and clinical diagnostics.
Several approaches to Raman imaging have been demonstrated that employ means to simultaneously record spatial and Raman spectral information. Almost exclusively, modern Raman imaging methods employ multi-channel charge-coupled device (CCD) detection. CCDs are employed to record two dimensions of the three-dimensional information inherent in Raman image data sets. Raman imaging systems can be differentiated by the means they employ to collect the third dimension of information. Raman imaging systems employing dispersive monochromators coupled to CCDs have been devised that rely on two-dimensional point scanning, one-dimensional line scanning, and spatial multiplexing. In addition, Michelson interferometers have been employed in point scanning systems, while a number of tunable filter spectrometers have been described in the past several years.
Of the imaging spectrometers that have been employed for Raman imaging, including liquid crystal tunable filters (LCTFs), acousto-optic tunable filters (AOTFs) and Fabry-Perot filters, LCTFs are the most effective. In general, tunable filter methods employ wide-field laser illumination in combination with multichannel detection. The two spatial dimensions of the image are recorded directly by the CCD camera, while the multispectral information is acquired by capturing images at discrete wavelengths selected by the tunable filter. Under computer control it is possible to collect a data set with a Raman spectrum at each pixel of the image. An advantage of tunable filters is that they provide image fidelity that is limited only by the number of pixels in the camera. As a result, the use of high-definition detectors allows the efficient collection of high-definition images. Prior to the introduction of LCTFs, a key limitation of tunable filters that had handicapped Raman microscopy had been the lack of the availability of tunable filters that simultaneously provided narrow spectral bandpass, broad free spectral range and high image quality. For example, AOTF Raman imaging systems provide high throughput and broad spectral coverage, but AOTFs have distinct limitations. AOTFs suffer from broad spectral bandpass, and imaging performance is degraded appreciably from the diffraction-limited conditions. In effect, AOTFs provide spectral resolution that is an order of magnitude worse than that of a typical Raman spectrometer, and spatial resolution that is approximately 2.5 times worse than the diffraction limit.
A better alternative to the AOTF is the LCTF. In general, LCTFs are electro-optically controllable spectral bandpass filters which can function from the visible to the near-infrared. A number of LCTF designs have been demonstrated for use in multispectral imaging. LCTFs based on the Lyot filter design have been used primarily as red-green-blue (RGB) color filters and fluorescence imaging filters. A nematic LCTF based on the design of the Lyot birefringent filter has been used in a Raman imaging system. The multistage Lyot filter is comprised of a fixed retardance birefringent element and a nematic liquid crystal wave plate placed between parallel linear polarizers. The nematic liquid crystal wave plates incorporated within the Lyot filter act as electronically controlled phase retarders. The LC wave plates can be adjusted over a continuous range of retardance levels, enabling continuous tunability of wavelength. In general, Lyot filters suffer from low peak transmittance. The two main sources of optical loss in the Lyot LCTFs are absorption in the polarizers and imperfect waveplate action arising from the use of simple .lambda./2 plates to construct the wide-field retarder stages. An LCTF based on a Fabry-Perot design has been demonstrated for Raman microscopy. However, Fabry-Perot filters suffer from low transmittance, low out of band rejection efficiency, limited free spectral range and low spectral bandpass (25 cm.sup.-1). In addition, Fabry-Perot filters are susceptible to thermal-induced drift in spectral bandpass unless contained in temperature-controlled housings.
John Evans described a `split-element` design that addresses the inefficiency of the Lyot design. The `split-element` design cuts the number of polarizers in half, plus one, reducing the absorbance of light due to the polarizers. In addition, the .lambda./2 waveplates are eliminated providing enhanced optical throughput. This yields an improved filter transmission ranging from 1.55-3.1 times that of the Lyot filter.
Unlike other tunable elements for Raman imaging, the LCTF is free of optical distortions, spectral leakage, or image shift with tuning. The first generation (Lyot) LCTFs were designed to operate with green laser excitation and operated only to 650 nm. Evans Split-Element LCTFs operate from 420-720 nm and from 650-1100 nm, as determined by the choice of polarizers. Operation in the red wavelength region has advantages, particularly for the analysis of biological systems. For example, operation in the red wavelength region provides enhanced fluorescence rejection when combined with efficient diode laser sources and takes full advantage of the enhanced red sensitivity of recent generation CCD detectors.
Compared to existing, non-imaging systems, the Raman LCTF system adds the powerful ability to visualize the distribution (morphology and architecture) of chemical species in heterogeneous samples with molecular compositional specificity. Raman images can be collected rapidly, non-invasively, with limited or no sample preparation, at high spatial resolution (&lt;250 nm) and with high fidelity where the spatial fidelity is limited by the number of pixels on the CCD detector. Most importantly, every image pixel has associated with it a Raman spectrum whose quality is comparable to that obtained with conventional non-imaging spectrometers.
Raman is so broadly applicable because most materials exhibit characteristic `fingerprint` Raman vibrational spectra. Generally accepted practice in performing Raman microscopy is to use non-imaging techniques such as a scanned laser Raman microspot, which yield spectral data but limited (or inefficient) collection of spatial data. Samples exhibiting complex morphologies and well characterized spectral bands are best studied using LCTF technology because of the inherent efficiency of analyzing all spatial channels simultaneously in a massively parallel fashion. The LCTF Raman chemical imaging measurement identifies the presence and/or location of an analyte species in a sample by imaging at the characteristic analyte Raman spectral bands. In general, it is not necessary to have a complete Raman spectrum at each image pixel in order to obtain meaningful and chemically relevant image contrast. This is especially due in part to the redundancy of a typical Raman spectrum. Often only several regions of the spectrum are needed to generate analyte-specific image contrast. The Evans Split-Element LCTF represents a breakthrough technology because it provides spectral resolution comparable to a single stage dispersive monochromator while also providing diffraction-limited spatial resolution. This performance is provided without moving mechanical parts in a computer controlled device which allows automated operation.
Cancer is a major cause of death worldwide. Early definitive detection and classification of cancerous growths is often crucial to successful treatment of this disease. Currently, several biopsy techniques are used as diagnostic methods after cancerous lesions are identified. In the case of breast cancer, lesions are typically identified with mammography or self breast exam. The most reliable method of diagnosis is examination of macroscopic-sized lesions. Macroanalysis is performed in conjunction with microscopic evaluation of paraffin-embedded biopsied tissue which is thin-sectioned to reveal microscale morphology.
The detection and diagnosis of cancer is typically accomplished through the use of optical microscopy. A tissue biopsy is obtained from a patient and that tissue is sectioned and stained. The prepared tissue is then analyzed by a trained oncologist who can differentiate between normal, malignant and benign tissue based on tissue morphology. Because of the tissue preparation required, this process is relatively slow. Moreover, the differentiation made by the oncologist is based on subtle morphological differences between normal, malignant and benign tissue based on tissue morphology. For this reason, there is a need for an imaging device that can rapidly and quantitively diagnose malignant and benign tissue.
Alternatives to traditional surgical biopsy include fine needle aspiration cytology and needle biopsy. These non-surgical techniques are becoming more prevalent as breast cancer diagnostic techniques because they are less invasive than biopsy techniques that harvest relatively large tissue masses. Fine needle aspiration cytology has the advantage of being a rapid, minimally invasive, non-surgical technique that retrieves isolated cells that are often adequate for evaluation of disease state. However, in fine needle biopsies intact breast tissue morphology is disrupted often leaving only cellular structure for analysis which is often less revealing of disease state. In contrast, needle biopsies use a much larger gauge needle which retrieve intact tissue samples that are better suited to morphology analysis. However, needle biopsies necessitate an outpatient surgical procedure and the resulting needle core sample must be embedded or frozen prior to analysis.
A variety of "optical biopsy" techniques have potential as non-invasive, highly sensitive approaches that will augment, or even be alternatives to current diagnostic methods for early detection of cancer, including breast cancer. Optical biopsies employ optical spectroscopy to non-invasively probe suspect tissue regions in situ, without extensive sample preparation. Diagnostic information is provided by the resultant spectroscopically unique signatures that allow differentiation of normal and abnormal tissues. One biodiagnostic technique is fluorescence optical biopsy. Due to the nonspecific nature of tissue autofluorescence and the need to add staining agents to augment the specificity of fluorescence approaches, this technique has limitations.
In contrast to other techniques, Raman spectroscopy holds promise as an optical biopsy technique that is anticipated to be broadly applicable for characterization of a variety of cancerous disease states. A number of researchers have shown that Raman spectroscopy has utility in differentiating normal vs. malignant tissue and differentiating normal vs. benign tissue. In general, the Raman spectra of malignant and benign tissues show an increase in protein content and a decrease in lipid content versus normal breast tissue, demonstrating that cancer disease states have a molecular basis for their origin.
However, difficulties exist when trying to use Raman spectroscopy alone to differentiate benign vs. malignant tissues due to the spectral similarities of these tissue types. In addition, Raman spectroscopy of breast tissue samples requires large numbers of cell populations. If only a small portion of the cells are cancerous, as in the early stages of lesion development, then Raman spectroscopy will be insensitive to the disease. It would be advantageous to have a technique capable of the spatial sensitivity needed for discrimination of cancerous from normal cells in early stage breast cancer diagnosis.
Chemical imaging based on optical spectroscopy, in particular Raman spectroscopy, provides the clinician with important information. Chemical imaging simultaneously provides image information on the size, shape and distribution (the image morphology) of molecular chemical species present within the sample. By utilizing molecular-specific imaging, based on chemical imaging, the trained clinician can make a determination on the disease-state of a tissue or cellular sample based on recognizable changes in morphology without the need for sample staining or modification.